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Event PyData Trójmiasto #37 2025-10-29
Dariusz Piotrowski – Senior Machine Learning Engineer (contractor) @ Amazon Robotics

Ever wondered what actually happens when you call an LLM API? This talk breaks down the inference pipeline from tokenization to text generation, explaining what's really going on under the hood. He will walk through the key sampling strategies and their parameters - temperature, top-p, top-k, beam search. We'll also cover performance tricks like quantization, KV caching, and prompt caching that can speed things up significantly. If time allows, we will also touch on some use-case-specific techniques like pass@k and majority voting.

LLM inference tokenization sampling strategies quantization kv caching prompt caching beam search
Marta Sienkiewicz – IT Release Manager @ Hapag-Lloyd

In her presentation she will show you a script in Python that combines some of her interests: urban planning and 3D modeling. You will learn how you can generate a 3D model of a city using Python, build123d library and OpenStreetMap data. If this is your first encounter with 3D modeling in Python, you may be surprised how simple the script actually is.

build123d openstreetmap Python
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